Towards a common C0-C2 mechanism: a critical evaluation of rate constants for syngas combustion kinetics

Since the pioneering studies of Tsang and Hampson [1], and of Baulch and co-workers [2, 3], the knowledge of elementary combustion kinetics has increased, largely due to more accurate theories, advanced computing facilities and progresses in experimental measurements [4]. However, no effort has been devoted to the collection and reinterpretation of this knowledge after the early 2000s. Starting in February 2017, we have collected and interpreted a very large number of direct and indirect rate constant measurements from the literature, as well as every state of the art theo-retical calculation available for 50 elementary reaction steps involved in H2/CO pyrolysis and combustion. A strong need for reconciling rate constant measurements and theory has emerged from this analysis. A significant number of the indirect measurements of rate constants and theoretical determinations seem, in fact, to disagree beyond the expected accuracy of parame-ters in the syngas subset. This is mostly due to the need for reconciliation of data and theory and the reinterpretation of the raw signals of the measurements with more accurate and better constrained models according to a careful iterative procedure. The joint effort of SMARTCAT partners at Politecnico di Milano, NUI Galway, ELTE Buda-pest and Denmark Technical University together with RWTH Aachen University (DE) and Argonne National Laboratory (USA), aims to propose a fundamentally based state of the art mechanism for syngas combustion, to serve as a reference for the entire combustion kinetics community. Due to many different reasons, models for real fuels available in the literature rely on more or less different C0-C2 subsets. These differences often do not have substantial im-pacts on the overall performances as different rates in the core mechanism are often counter-balanced by different rates in the model subset relating to heavier fuels. This leads to very sim-ilar radical distributions and therefore in similar macroscopic behavior. However, the adoption of a fundamentally based common core mechanism will constitute a substantial thrust to in-crease the robustness of higher molecular weight fuel’s kinetics

Insights into the behaviour of systems biology models from dynamic sensitivity and identifiability analysis: a case study of an NF-kB signaling pathway

Mathematical modelling offers a variety of useful techniques to help in understanding the intrinsic behaviour of complex signal transduction networks. From the system engineering point of view, the dynamics of metabolic and signal transduction models can always be described by nonlinear ordinary differential equations (ODEs) following mass balance principles. Based on the state-space formulation, many methods from the area of automatic control can conveniently be applied to the modelling, analysis and design of cell networks. In the present study, dynamic sensitivity analysis is performed on a model of the IB-NF-B signal pathway system. Univariate analysis of the Euclidean-form overall sensitivities shows that only 8 out of the 64 parameters in the model have major influence on the nuclear NF-B oscillations. The sensitivity matrix is then used to address correlation analysis, identifiability assessment and measurement set selection within the framework of least squares estimation and multivariate analysis. It is shown that certain pairs of parameters are exactly or highly correlated to each other in terms of their effects on the measured variables. The experimental design strategy provides guidance on which proteins should best be considered for measurement such that the unknown parameters can be estimated with the best statistical precision. The whole analysis scheme we describe provides efficient parameter estimation techniques for complex cell networks

Molecular Design and Functional Control of Novel Self-Oscillating Polymers

If we could realize an autonomous polymer system driven under biological conditions by a tailor-made molecular design, human beings could create unprecedented biomimetic functions and materials such as heartbeats, autonomous peristaltic pumps, etc. In order to achieve this objective, we have investigated the molecular design of such a polymer system. As a result, we were the first to demonstrate a self-oscillating polymer system driven in a solution where only malonic acid existed, which could convert the chemical energy of the Belousov-Zhabotinsky (BZ) reaction into a change in the conformation of the polymer chain. To cause the self-oscillation in solution, we have attempted to construct a built-in system where the required BZ system substrates other than the organic acid are incorporated into the polymer itself. That is, the novel polymer chain incorporated the metal catalyst of the BZ reaction, a pH-control site and an oxidant supply site at the same time. As a result of introducing the pH control and oxidant supply sites into the conventional-type self-oscillating polymer chain, the novel polymer chain caused aggregation-disaggregation self-oscillations in the solution. We clarified that the period of the self-oscillation of the novel self-oscillating polymer chain was proportional to the concentration of the malonic acid. Therefore, the concentration of the malonic acid can be determined by measuring the period of the novel self-oscillating polymer solution. In this review, we introduce the detailed molecular design of the novel self-oscillating polymer chain and its self-oscillating behavior. Moreover, we report an autonomous self-oscillating polymer gel actuator that causes a bending-stretching motion under the constant conditions

Asymptotology of Chemical Reaction Networks

The concept of the limiting step is extended to the asymptotology of multiscale reaction networks. Complete theory for linear networks with well separated reaction rate constants is developed. We present algorithms for explicit approximations of eigenvalues and eigenvectors of kinetic matrix. Accuracy of estimates is proven. Performance of the algorithms is demonstrated on simple examples. Application of algorithms to nonlinear systems is discussed.Comment: 23 pages, 8 figures, 84 refs, Corrected Journal Versio

Depressive symptoms are associated with objectively measured sleep parameters in kidney transplant recipients

STUDY OBJECTIVES: Both depression and sleep complaints are very prevalent among kidney transplant (kTx) recipients. However, details of the complex relationship between sleep and depression in this population are not well documented. Thus, we investigated the association between depressive symptoms and sleep macrostructure parameters among prevalent kTx recipients.  METHODS: Ninety-five kTx recipients participated in the study (54 males, mean age 51 ± 13 y, body mass index 26 ± 4 kg/m2, estimated glomerular filtration rate 53 ± 19 ml/min/1.73 m2). Symptoms of depression were assessed by the Center for Epidemiologic Studies - Depression Scale (CES-D). After 1-night polysomnography each recording was visually scored and sleep macrostructure was analyzed.  RESULTS: The CES-D score was significantly associated with the amount of stage 2 sleep (r = 0.20, p 0.05). In multivariable linear regression models the CES-D score was independently associated with the amount of stage 2 sleep (β: 0.205; confidence interval: 0.001-0.409; p = 0.05) and REM latency (β: 0.234; confidence interval: 0.001-0.468; p = 0.05) after adjustment for potential confounders.  CONCLUSIONS: Depressive symptoms among kTx recipients are associated with increased amount of stage 2 sleep and prolonged REM latency. Further studies are needed to confirm our findings and understand potential clinical implications